Detection of malware using an instrumented virtual machine environment

ABSTRACT

Various techniques for detection of malware using an instrumented virtual machine environment are disclosed. In some embodiments, detection of malware using an instrumented virtual machine environment includes instantiating a first virtual machine in the instrumented virtual machine environment, in which the first virtual machine is configured to support installation of two or more versions of a resource; installing a first version of the resource on the first virtual machine and monitoring the instrumented virtual machine environment while executing the first version of the resource with a malware sample opened using the first version of the resource; and installing a second version of the resource on the first virtual machine and monitoring the instrumented virtual machine environment while executing the second version of the resource with the malware sample opened using the second version of the resource.

CROSS REFERENCE TO OTHER APPLICATIONS

This application is a continuation of co-pending U.S. patent applicationSer. No. 14/331,113, entitled DETECTION OF MALWARE USING AN INSTRUMENTEDVIRTUAL MACHINE ENVIRONMENT, filed Jul. 14, 2014, which is incorporatedherein by reference for all purposes.

BACKGROUND OF THE INVENTION

A firewall generally protects networks from unauthorized access whilepermitting authorized communications to pass through the firewall. Afirewall is typically a device or a set of devices, or software executedon a device, such as a computer, that provides a firewall function fornetwork access. For example, firewalls can be integrated into operatingsystems of devices (e.g., computers, smart phones, or other types ofnetwork communication capable devices). Firewalls can also be integratedinto or executed as software on computer servers, gateways,network/routing devices (e.g., network routers), or data appliances(e.g., security appliances or other types of special purpose devices).

Firewalls typically deny or permit network transmission based on a setof rules. These sets of rules are often referred to as policies. Forexample, a firewall can filter inbound traffic by applying a set ofrules or policies. A firewall can also filter outbound traffic byapplying a set of rules or policies. Firewalls can also be capable ofperforming basic routing functions.

BRIEF DESCRIPTION OF THE DRAWINGS

Various embodiments of the invention are disclosed in the followingdetailed description and the accompanying drawings.

FIG. 1 is a functional diagram of an architecture for providingdetection of malware using an instrumented virtual machine environmentin accordance with some embodiments.

FIG. 2 illustrates a data appliance in accordance with some embodiments.

FIG. 3 is a flow diagram of a process for providing detection of malwareusing an instrumented virtual machine environment in accordance withsome embodiments.

FIG. 4 is another flow diagram of a process for providing detection ofmalware using an instrumented virtual machine environment in accordancewith some embodiments.

FIG. 5 is another flow diagram of a process for providing detection ofmalware using an instrumented virtual machine environment in accordancewith some embodiments.

DETAILED DESCRIPTION

The invention can be implemented in numerous ways, including as aprocess; an apparatus; a system; a composition of matter; a computerprogram product embodied on a computer readable storage medium; and/or aprocessor, such as a processor configured to execute instructions storedon and/or provided by a memory coupled to the processor. In thisspecification, these implementations, or any other form that theinvention may take, may be referred to as techniques. In general, theorder of the steps of disclosed processes may be altered within thescope of the invention. Unless stated otherwise, a component such as aprocessor or a memory described as being configured to perform a taskmay be implemented as a general component that is temporarily configuredto perform the task at a given time or a specific component that ismanufactured to perform the task. As used herein, the term ‘processor’refers to one or more devices, circuits, and/or processing coresconfigured to process data, such as computer program instructions.

A detailed description of one or more embodiments of the invention isprovided below along with accompanying figures that illustrate theprinciples of the invention. The invention is described in connectionwith such embodiments, but the invention is not limited to anyembodiment. The scope of the invention is limited only by the claims andthe invention encompasses numerous alternatives, modifications andequivalents. Numerous specific details are set forth in the followingdescription in order to provide a thorough understanding of theinvention. These details are provided for the purpose of example and theinvention may be practiced according to the claims without some or allof these specific details. For the purpose of clarity, technicalmaterial that is known in the technical fields related to the inventionhas not been described in detail so that the invention is notunnecessarily obscured.

A firewall generally protects networks from unauthorized access whilepermitting authorized communications to pass through the firewall. Afirewall is typically a device, a set of devices, or software executedon a device that provides a firewall function for network access. Forexample, a firewall can be integrated into operating systems of devices(e.g., computers, smart phones, or other types of network communicationcapable devices). A firewall can also be integrated into or executed assoftware applications on various types of devices or security devices,such as computer servers, gateways, network/routing devices (e.g.,network routers), or data appliances (e.g., security appliances or othertypes of special purpose devices).

Firewalls typically deny or permit network transmission based on a setof rules. These sets of rules are often referred to as policies (e.g.,network policies or network security policies). For example, a firewallcan filter inbound traffic by applying a set of rules or policies toprevent unwanted outside traffic from reaching protected devices. Afirewall can also filter outbound traffic by applying a set of rules orpolicies (e.g., allow, block, monitor, notify or log, and/or otheractions can be specified in firewall rules or firewall policies, whichcan be triggered based on various criteria, such as described herein).

Security devices (e.g., security appliances, security gateways, securityservices, and/or other security devices) can include various securityfunctions (e.g., firewall, anti-malware, intrusion prevention/detection,proxy, and/or other security functions), networking functions (e.g.,routing, Quality of Service (QoS), workload balancing of network relatedresources, and/or other networking functions), and/or other functions.For example, routing functions can be based on source information (e.g.,IP address and port), destination information (e.g., IP address andport), and protocol information.

A basic packet filtering firewall filters network communication trafficby inspecting individual packets transmitted over a network (e.g.,packet filtering firewalls or first generation firewalls, which arestateless packet filtering firewalls). Stateless packet filteringfirewalls typically inspect the individual packets themselves and applyrules based on the inspected packets (e.g., using a combination of apacket's source and destination address information, protocolinformation, and a port number).

Application firewalls can also perform application layer filtering(e.g., using application layer filtering firewalls or second generationfirewalls, which work on the application level of the TCP/IP stack).Application layer filtering firewalls or application firewalls cangenerally identify certain applications and protocols (e.g., webbrowsing using HyperText Transfer Protocol (HTTP), a Domain Name System(DNS) request, a file transfer using File Transfer Protocol (FTP), andvarious other types of applications and other protocols, such as Telnet,DHCP, TCP, UDP, and TFTP (GSS)). For example, application firewalls canblock unauthorized protocols that attempt to communicate over a standardport (e.g., an unauthorized/out of policy protocol attempting to sneakthrough by using a non-standard port for that protocol can generally beidentified using application firewalls).

Stateful firewalls can also perform stateful-based packet inspection inwhich each packet is examined within the context of a series of packetsassociated with that network transmission's flow of packets/packet flow(e.g., stateful firewalls or third generation firewalls). This firewalltechnique is generally referred to as a stateful packet inspection as itmaintains records of all connections passing through the firewall and isable to determine whether a packet is the start of a new connection, apart of an existing connection, or is an invalid packet. For example,the state of a connection can itself be one of the criteria thattriggers a rule within a policy.

Advanced or next generation firewalls can perform stateless and statefulpacket filtering and application layer filtering as discussed above.Next generation firewalls can also perform additional firewalltechniques. For example, certain newer firewalls sometimes referred toas advanced or next generation firewalls can also identify users andcontent. In particular, certain next generation firewalls are expandingthe list of applications that these firewalls can automatically identifyto thousands of applications. Examples of such next generation firewallsare commercially available from Palo Alto Networks, Inc. (e.g., PaloAlto Networks' PA Series firewalls).

For example, Palo Alto Networks' next generation firewalls enableenterprises to identify and control applications, users, and content—notjust ports, IP addresses, and packets—using various identificationtechnologies, such as the following: APP-ID for accurate applicationidentification, User-ID for user identification (e.g., by user or usergroup), and Content-ID for real-time content scanning (e.g., controlsweb surfing and limits data and file transfers). These identificationtechnologies allow enterprises to securely enable application usageusing business-relevant concepts, instead of following the traditionalapproach offered by traditional port-blocking firewalls. Also, specialpurpose hardware for next generation firewalls implemented, for example,as dedicated appliances generally provide higher performance levels forapplication inspection than software executed on general purposehardware (e.g., such as security appliances provided by Palo AltoNetworks, Inc., which utilize dedicated, function specific processingthat is tightly integrated with a single-pass software engine tomaximize network throughput while minimizing latency).

Dynamic Analysis to Identify and Block Unknown Threats

However, a significant challenge for security detection techniques is toidentify threats (e.g., malware, which refers to malicious programs,such as programs attempting to perform malicious or undesired actions)attempting to use new exploits, such as zero-day threats that have notpreviously been identified (e.g., targeted and unknown threats). Forexample, a new zero-day threat and/or an Advanced Persistent Threat(APT) (e.g., various techniques using malware to exploit vulnerabilitiesin systems and often using an external command and control forcontinuously monitoring and extracting data from a specific target,often using stealthy, persistent methods that can evade traditionalsecurity measures, such as signature-based malware detection measures)that has not previously been identified (e.g., for which no signatureyet exists) can exploit new or unresolved vulnerabilities in anapplication or operation system.

In particular, modern attackers are increasingly using targeted and newunknown variants of malware to avoid detection by traditional securitysolutions. For example, advanced security threats (e.g., advancedcyber-attacks) are employing stealthy, persistent methods to evadetraditional security measures. Skilled adversaries demand that modernsecurity teams re-evaluate their basic assumptions that traditionalintrusion prevention systems, antivirus, and single-purpose sandboxappliances are up to the task of defeating advanced security threats,such as APTs.

To address this, new and improved techniques are needed to efficientlyand effectively identify such new and evolving malware. For example, byexecuting suspect files (e.g., malware samples) in a virtual environment(e.g., an instrumented virtual environment, which is sometimes alsoreferred to as using a sandbox analysis of malware samples, which can beunknown threats) and observing their behavior, such malware can bequickly and accurately identified, even if the malware sample has notbeen previously analyzed and detected.

Once a file is deemed malicious (e.g., a malware sample is deemed to bemalware), protections can be automatically generated using a cloudsecurity service (e.g., implementing a dynamic security analysis ofmalware samples in a scalable cloud-based, virtual environment todirectly observe the behavior of potentially malicious malware andexploits) to be delivered to subscribers of the cloud security service(e.g., within minutes or hours of detection). For example, suchtechniques can also be used to forensically determine who/what wastargeted, including the application used in the delivery, any UniformResource Locator addresses (URLs) that were part of the attack, etc.(e.g., when an unknown threat is discovered, techniques disclosed hereincan automatically generate protections to block the threat across thecyber kill-chain, sharing these updates with subscribers of the cloudsecurity service within minutes or hours of detection, such that thesequick updates can stop rapidly spreading malware, as well as identifyand block the proliferation of potential future variants without anyadditional action or analysis). As disclosed herein, the cloud securityservice identifies unknown malware, zero-day exploits, and AdvancedPersistent Threats (APTs) by directly executing them in a scalablecloud-based, virtual sandbox environment (e.g., an instrumented virtualenvironment). Also, the cloud security service automatically creates anddisseminates protections in near real-time to help security teams meetthe challenge of advanced security threats. In an exampleimplementation, cloud security service extends the next-generationfirewall platform that natively classifies all traffic across manydifferent applications, and the cloud security service can apply abehavioral analysis regardless of ports or encryption, including fullvisibility into web traffic, email protocols (SMTP, IMAP, POP), FTP,SMB, and/or other protocols to facilitate detection and disseminationprotections in near real-time to respond to such advanced securitythreats.

However, detection of malware using an instrumented virtual environmentcan be costly in terms of required computing resources (e.g., includingprocessor and memory usage and computing time) used to perform dynamicsecurity analysis using such an instrumented virtual environment. Forexample, existing sandbox approaches to malware detection typically onlyinstall one version of software (e.g., applications or other software)per virtual machine instance, which can be inefficient and/or limitmalware detection rates (e.g., as certain malware may only exploitvulnerabilities in certain versions of software). As another example,some other existing approaches execute multiple virtual machineinstances with different software configurations (e.g., sequentially orsimultaneously), but performing such approaches can be very resourceconsuming and/or time consuming.

Thus, what are needed are new and improved techniques for detection ofmalware using an instrumented virtual machine environment. For example,various techniques described herein can more efficiently performdetection of malware using an instrumented virtual machine environment(e.g., more efficiently using computing resources, including processorand memory usage and computing time, used to perform dynamic securityanalysis using such an instrumented virtual environment). In addition,these techniques described herein can also provide an enhanced detectionrate of malware using an instrumented virtual machine environment thatis performed more efficiently as further discussed below.

Accordingly, various techniques for detection of malware using aninstrumented virtual machine environment are disclosed. In someembodiments, detection of malware using an instrumented virtual machineenvironment includes instantiating a first virtual machine in theinstrumented virtual machine environment, in which the first virtualmachine is configured to support installation of two or more versions ofa resource; installing a first version of the resource on the firstvirtual machine and monitoring the instrumented virtual machineenvironment while executing the first version of the resource with amalware sample opened using the first version of the resource; andinstalling a second version of the resource on the first virtual machineand monitoring the instrumented virtual machine environment whileexecuting the second version of the resource with the malware sampleopened using the second version of the resource. In an exampleimplementation, the second version of the resource is installed on thefirst virtual machine without having to re-instantiate the first virtualmachine. In some embodiments, any items that are associated with aparticular version of the resource can be renamed in order to conceal(e.g., hide) the presence of that version of the resource having beeninstalled in the system environment. For example, any file related itemsand/or registry key related items can be renamed and various additionaltechniques can be performed for handling any new process and/or servicerelated items as further described below, such that the systemenvironment can be returned to an appearance of a clean state as wouldbe apparent to another version of the resource (e.g., as any itemsassociated with the first version of the resource have been hidden fromdetection by the renaming of such items to different names/directoriesand/or renaming any such items to different registry key name/paths,and/or starting/stopping of any processes and/or services, such asfurther described below with respect to FIG. 3).

For example, the resource can include an executable application, and themalware sample can include a file in a format that is compatible withthe executable application (e.g., the application can open the malwaresample file). In particular, the instrumented virtual machineenvironment is monitored while executing each version of the resourcewith the malware sample opened using each version of the application forat least a predetermined period of time or until malicious behavior isdetected (e.g., if there are four versions of the application, then asix minute period of time can be equally allocated among each of thefour versions of the application, such that the malware sample is openedusing each of the four versions of the malware sample and monitored forapproximately one minute and thirty seconds).

In some embodiments, detection of malware using an instrumented virtualmachine environment further includes storing a plurality of installedversions of the resource using dummy file names for one or more registryfiles and one or more executable files associated with the resource; andfor each version of the resource to be executed, renaming one or more ofthe dummy file names associated with the version of the resource beingexecuted to a predetermined file name (e.g., the dummy file names thatare needed for properly executing a selected version of the applicationcan be renamed to expected file names so that the selected version ofthe application can execute properly).

In some embodiments, detection of malware using an instrumented virtualmachine environment further includes preloading one or more system files(e.g., required libraries, such as dynamically loaded libraries (DLLs))that are used by the first version of the resource and/or the secondversion of the resource into a new resource system file locationdirectory; and overriding an installer for the resource to redirect theinstaller to the new resource system file location directory.

In some embodiments, detection of malware using an instrumented virtualmachine environment further includes receiving the malware sample at acloud security service from a security device, in which the instrumentedvirtual environment is monitored during execution of each version of theresource with the malware sample opened using each version of theresource to determine whether the malware sample indicates potentiallymalicious behavior

In some embodiments, detection of malware using an instrumented virtualmachine environment further includes capturing network traffic whilemonitoring the instrumented virtual machine environment. In someembodiments, the instrumented virtual machine environment is configuredto include at least one kernel hook and/or at least one user level hook.In some embodiments, the instrumented virtual machine environment isconfigured to include at least one honey file.

Accordingly, various techniques for detection of malware using aninstrumented virtual machine environment are disclosed. For example,using such techniques can facilitate an efficient and enhanced detectionof malware using an instrumented virtual machine environment. As will beapparent to one skilled in the art in view of the various techniques andembodiments described herein, while the various techniques describedherein for detection of malware using an instrumented virtual machineenvironment are described with respect to virtual environments using asecurity service (e.g., a cloud security service), such techniques cansimilarly be applied to various other security environments, including,for example, performed in part or completely using security devices suchas appliances, gateways, servers, and/or other security platformscapable of implementing various virtual environment techniques disclosedherein.

FIG. 1 is a functional diagram of an architecture for providingdetection of malware using an instrumented virtual machine environmentin accordance with some embodiments. For example, such an environmentcan detect and prevent malware from causing harm (e.g., malicioussoftware can include any executable program, such as active content,executable code, and scripts, that can interfere with operation of acomputing device or computer network, attempt unauthorized access ofdata or components of a computing device, and/or perform various othermalicious, unauthorized, and/or undesirable activities). In particular,a variety of attempts by a malicious individual to propagate malware(e.g., malware 130) via system 120 are described, as are techniques forthwarting that propagation or execution of such malware in protectednetwork computing environments, such as for protecting computing deviceswithin an enterprise network 110.

In the example shown in FIG. 1, client devices 104, 106, and 108 are alaptop computer, a desktop computer, and a tablet (respectively) presentin an enterprise network 110. Data appliance 102 is configured toenforce policies regarding communications between clients, such asclients 104 and 106, and nodes outside of enterprise network 110 (e.g.,reachable via external network 118, such as the Internet). Examples ofsuch policies include ones governing traffic shaping, quality ofservice, and routing of traffic. Other examples of policies includesecurity policies such as ones requiring the scanning for threats inincoming (and/or outgoing) email attachments, website downloads, filesexchanged through instant messaging programs, and/or other filetransfers. In some embodiments, appliance 102 is also configured toenforce policies with respect to traffic that stays within enterprisenetwork 110.

Appliance 102 can take a variety of forms. For example, appliance 102can be a dedicated device or set of devices. The functionality providedby appliance 102 can also be integrated into or executed as software ona general purpose computer, a computer server, a gateway, and/or anetwork/routing device. For example, in some embodiments, servicesprovided by data appliance 102 are instead (or in addition) provided toclient 104 by software executing on client 104.

Whenever appliance 102 is described as performing a task, a singlecomponent, a subset of components, or all components of appliance 102may cooperate to perform the task. Similarly, whenever a component ofappliance 102 is described as performing a task, a subcomponent mayperform the task and/or the component may perform the task inconjunction with other components. In various embodiments, portions ofappliance 102 are provided by one or more third parties. Depending onfactors such as the amount of computing resources available to appliance102, various logical components and/or features of appliance 102 may beomitted and the techniques described herein adapted accordingly.Similarly, additional logical components/features can be added to system102 as applicable.

As will be described in more detail below, appliance 102 can beconfigured to work in cooperation with one or more virtual machineservers (112, 124) to perform malware analysis/prevention, includingvarious techniques for providing detection of malware using aninstrumented virtual machine environment as disclosed herein. As oneexample, data appliance 102 can be configured to provide a copy ofmalware 130 (e.g., a malware sample, which can include potentiallymalicious content) to one or more of the virtual machine servers forreal-time analysis. As another example, a cloud security service 122 canprovide a list of signatures of known-malicious documents to appliance102 as part of a subscription. Those signatures can be generated byservice 122 in conjunction with the techniques described herein. Forexample, if service 122 identifies a new malware associated with themalware sample received from a data appliance (e.g., data appliance 102or another data appliance), such as using various techniques forproviding detection of malware using an instrumented virtual machineenvironment as disclosed herein, cloud security service 122 canautomatically generate a new signature for the newly identified malwareand send the new signature to various subscribers (e.g., data appliance102 and various other data appliances that receive subscription-basedsignature updates).

An example of a virtual machine server is a physical machine comprisingcommercially available server-class hardware (e.g., a multi-coreprocessor such as a dual 6-core Intel® processor with Hyper-Threading, 4or more Gigabytes of RAM such as a 128 GB RAM, a system disk such as a120 GB SSD, and one or more Gigabit network interface adapters) thatruns commercially available virtualization software, such as VMwareESXi, Citrix XenServer, or Microsoft Hyper-V (e.g., such a VMenvironment can emulate the Windows® XP operating system environmentusing the dual 6-core Intel® processor with Hyper-Threading and 512 MBof RAM, the Windows® 7 operating system environment using the dual6-core Intel® processor with Hyper-Threading and 1 GB of RAM, and/orother operating system environments and/or using different hardwarecapacity/components). The virtual machine servers may be separate from,but in communication with, data appliance 102, as shown in FIG. 1. Avirtual machine server may also perform some or all of the functions ofdata appliance 102, and a separate data appliance 102 is omitted asapplicable. Further, a virtual machine server may be under the controlof the same entity that administers data appliance 102 (e.g., virtualmachine server 112); the virtual machine server may also be provided bya third party (e.g., virtual machine server 124, which can be configuredto provide services to appliance 102 via third party service 122). Insome embodiments, data appliance 102 is configured to use one or theother of virtual machine servers 112 and 124 for malware analysis. Inother embodiments, data appliance 102 is configured to use the servicesof both servers (and/or additional servers not shown). Thus, in someimplementations, the cloud security service can be delivered either as apublic cloud or as a private cloud (e.g., deployed locally on anenterprise network using a locally deployed data appliance or server).

In some embodiments, the virtual machine server 124 is configured toimplement various emulation-based techniques for providing detection ofmalware using an instrumented virtual machine environment as describedherein with respect to various embodiments (e.g., implemented usinginstrumented VM environments 126 and 128, which can be executed by cloudsecurity service 122 and/or malware analysis system 132, such asdescribed below with respect to FIGS. 3 and 4, and with respect tovarious other embodiments disclosed herein). For example, the virtualmachine server 124 can provide an instrumented virtual machineenvironment capable of performing the various techniques as describedherein. These instrumented virtual machine (VM) environments 126 and 128can include, for example, various user level hooks and/or kernel levelhooks in the emulated execution environment to facilitate the monitoringof various program behaviors during execution in the virtual environment(e.g., instrumented VM environments, such as described above) and to logsuch monitored program behaviors for analysis based on the varioustechniques described herein with respect to various embodiments. Also,in some cases, multiple instances of a malware sample can be performedusing multiple VM environments to perform various tests and/or executeusing different execution environments (e.g., different versions of anoperating system (OS) environment, different versions of an application,etc.).

FIG. 2 illustrates a data appliance in accordance with some embodiments.The example shown is a representation of physical components that areincluded in data appliance 102, in some embodiments. Specifically, dataappliance 102 (e.g., a device that performs various security relatedfunctions, such as a security device, which can be in the form of, forexample, a security appliance, security gateway, security server, and/oranother form of a security device) includes a high performancemulti-core CPU 202 and RAM 204. Data appliance 102 also includes astorage 210 (such as one or more hard disks), which is used to storepolicy and other configuration information. Data appliance 102 can alsoinclude one or more optional hardware accelerators. For example, dataappliance 102 can include a cryptographic engine 206 configured toperform encryption and decryption operations, and one or more FPGAs 208configured to perform matching, act as network processors, and/orperform other tasks.

Applying Instrumented Virtual Machines to Analyze Malware Samples

An instrumented virtual machine (VM) can be used to perform behaviorprofiling (e.g., in a VM sandbox environment) using variousheuristic-based analysis techniques that can be performed in real-timeduring execution of the program in the instrumented virtual environment,such as during a file transfer (e.g., during an active file/attachmentdownload) and/or on files previously collected (e.g., a collection offiles submitted for batch analysis). Documents, executables, and otherforms of potentially malicious content (e.g., to be evaluated) arereferred to herein as “malware samples” or just “samples.”

As one example, suppose a malicious user of system 120 sends an emailmessage to a user of client 104 that includes a suspicious or maliciousattachment. The attachment may be an executable (e.g., having a fileextension of, for example, .exe or .js or some other executable relatedfile extension) and may also be a document (e.g., having a fileextension of, for example, .doc or .pdf or some other document relatedfile extension). The message is received by data appliance 102, whichdetermines whether a signature for the attachment is present on dataappliance 102. A signature, if present, can indicate that the attachmentis known to be safe, and can also indicate that the attachment is knownto be malicious. If no signature for the attachment is found, dataappliance 102 is configured to provide the attachment to a virtualmachine server, such as virtual machine server 112, for analysis.

Virtual machine server 112 is configured to execute (e.g., or open, asapplicable, using an appropriate application to open the file using anapplication that is compatible with opening that file format) theattachment in one or more virtual machines, such as virtual machines 114and 116 (e.g., instantiated virtual machines in the instrumented virtualmachine environment). The virtual machines may all execute the sameoperating system (e.g., Microsoft Windows) or may execute differentoperating systems or versions thereof (e.g., with VM 116 emulating anAndroid operating system or some other operating system). In someembodiments, the VM(s) chosen to analyze the attachment are selected tomatch the operating system of the intended recipient of the attachmentbeing analyzed (e.g., the operating system of client 104). Observedbehaviors resulting from executing/opening the attachment (e.g., toanalyze various behaviors while executing/opening the attachment in theinstrumented VM environment) are logged and analyzed for indicationsthat the attachment is potentially malicious or malicious.

As discussed above, instantiating multiple virtual machine instances forperforming analysis of a given malware sample can be expensive from acomputing resources perspective and can also be inefficient from acompute time perspective (e.g., due to the time required to launch aninstance of a VM with desired resources, etc., and CPU and memoryrequirements for executing multiple such VMs on an appliance/server).Thus, to improve performance of malware detection using an instrumentedvirtual machine environment, in some embodiments, a virtual machine isinstantiated in the instrumented virtual machine environment (e.g.,virtual machines 114 and/or 116), in which the virtual machine isconfigured to support installation of two or more versions of a resource(e.g., an executable application that can be used for opening themalware sample which can include a file in a format that is compatiblewith the executable application, such as two or more versions of AdobeAcrobat® for opening a malware sample that is a PDF file format (.pdf)or two or more versions of Microsoft Word® for opening a malware samplethat is a Word document file format (.doc), etc.). Such a virtualmachine can then be used to install a first version of the resource andmonitor the instrumented virtual machine environment while executing thefirst version of the resource with the malware sample opened using thefirst version of the resource. This virtual machine can then also beused to install a second version of the resource on the first virtualmachine and monitor the instrumented virtual machine environment whileexecuting the second version of the resource with the malware sampleopened using the second version of the resource. As such, theinstrumented virtual machine environment can be monitored whileexecuting each version of the resource with the malware sample openedusing each version of the resource for at least a predetermined periodof time or until malicious behavior is detected (e.g., if there are fourversions of the application, then a six minute period of time can beequally allocated among each of the four versions of the application,such that the malware sample is opened using each of the four versionsof the malware sample and monitored for approximately 1 minute and 30seconds). This approach allows for an efficient analysis of the malwaresample using multiple different versions of the resource for opening themalware sample and monitoring behavior in the instrumented virtualenvironment without having to re-instantiate the virtual machine toinstall and execute such different versions of the resource (e.g.,executable application versions).

In some embodiments, such VM-based analysis techniques are performed bythe VM server (e.g., VM server 112). In other embodiments, such VM-basedanalysis techniques are performed at least in part by appliance 102(e.g., or in some cases, such VM-based analysis techniques can beperformed completely by the appliance 102). The malware analysis andenforcement functionality illustrated in FIG. 1 as being provided bydata appliance 102 and VM server 112 is also referred to herein as beingprovided by malware analysis system 132. As explained above, portions ofmalware analysis system 132 may be provided by multiple distinctdevices, but may also be provided on a single platform, as applicable.

If the malware sample (e.g., attachment) is determined to be malicious,appliance 102 can automatically block the file download based on theanalysis result. Further, in some embodiments, a signature can begenerated and distributed (e.g., to other data appliances) toautomatically block future file transfer requests to download the filedetermined to be malicious.

Techniques for Providing an Efficient and Enhanced Detection of MalwareUsing an Instrumented Virtual Machine Environment

Malware often leverages exploits that are specific to a particularsystem configuration or set of system configurations. For example,malware 130 might be able to successfully compromise a computer systemrunning a particular operating system version and/or a particularapplication version, such as Adobe Acrobat® Version 9.0 (e.g., runningon client 104), but be unable to compromise a computer system runningany versions of Adobe Acrobat® Version 10.0 (e.g., running on client106). If the only virtual machine used to evaluate malware 130 is aninstrumented virtual machine environment with Adobe Acrobat® Version 9.0installed, then the malicious nature of malware 130 might not bediscovered. As another example, malware 130 might be able tosuccessfully compromise a system upon which a particular combination ofsoftware is installed (e.g., a specific version of Internet Explorerwith a specific version of Java). If the only virtual machine image(s)used to evaluate malware 130 include only one but not both applications,or include different versions of those applications, then the maliciousnature of malware 130 might not be discovered.

Some computing environments are relatively homogenous. For example,every employee at a startup might be issued the same laptop, running thesame operating system, and with the same base applications installed.More typically, however, a range of different platforms andconfigurations is supported (e.g., in an enterprise environment).Further, certain employees (e.g., in the Finance Department) may needaccess to additional software (e.g., Microsoft Access®) not included onthe systems of other users. And, employees are often allowed tocustomize their systems, e.g., by adding or removing software.

Suppose malware 130 targets Microsoft Windows systems. Further supposethat the IT Department of Acme Company supports the following: Windows 7operating system with either Internet Explorer 9 or 10, and any ofMicrosoft Office 2007 and 2010 installed. An Acme Company employee maythus potentially be opening malware 130 on any of four differentofficially supported Windows system and application versionconfigurations. Using the techniques described herein, malware analysissystem 132 can efficiently evaluate malware 130 using a single virtualmachine instance that can then install and execute each of these fourpotential application version configurations and will be able to detectthat malware 130 is malicious. In particular, this approach to providingdynamic security analysis using an instrumented virtual machineenvironment is efficiently performed in this case without having tore-instantiate the virtual machine instance by installing and executingeach of these four different combinations of application versions in thesingle virtual machine instance for the Windows 7 operating system. Aswould be apparent to those of ordinary skill in the art, this approachis more efficient, because such an approach requires less computingresources and time than instantiating and executing four differentvirtual machine instances corresponding to each of the four potentialapplication version configurations in order to detect that malware 130is malicious. Thus, as will be described in more detail below,performing runtime installations of different resources (e.g., differentversions of one or more applications) can efficiently be made to asingle virtual machine instance (e.g., to efficiently test multipledifferent potential system configurations) to facilitate an efficientdetection of and enhanced detection rate of malware using aninstrumented virtual machine environment.

A variety of techniques for detection of malware using an instrumentedvirtual machine environment will be described in conjunction with FIG.3.

FIG. 3 is a flow diagram of a process for providing detection of malwareusing an instrumented virtual machine environment in accordance withsome embodiments. In various embodiments, process 300 is performed bymalware analysis system 132. The process begins at 302 when candidatemalware (e.g., a malware sample) is received. As one example, candidatemalware is received at 302 when an email (e.g., including an attachment)is received by data appliance 102 from system 120. As another example,data appliance 102 can be configured to transmit the attachment toservice 122 for analysis. In that scenario, the candidate malware isreceived by cloud security service 122 at 302.

At 304, instantiating a first virtual machine (i.e., launching a singlevirtual machine instance for execution) in the instrumented virtualmachine environment is performed. In particular, the first virtualmachine is configured to support installation of two or more versions ofa resource. For example, the candidate malware can be executed in one ofvirtual machines 114-116 and any behaviors logged for analysis by system132. As another example, the candidate malware can be executed in one ofvirtual machines 126-128 and analyzed by cloud security service 122.

At 306, installing a first version of a resource on the first virtualmachine and monitoring the instrumented virtual machine environmentwhile executing the first version of the resource with a malware sampleopened using the first version of the resource is performed. Forexample, the candidate malware can be analyzed by opening the candidatemalware using the first version of the resource and monitoring behaviorsusing the instrumented virtual machine environment (e.g., for apredetermined period of time and/or until malicious behavior/activity isdetected). In an example implementation, the first virtual machineinstance can be configured to include a set of instructions (e.g.,startup instructions, such as in an autoexec.bat file), such as a set ofinstructions to install the first version of the resource and to openthe candidate malware using the first version of the resource.

At 308, installing a second version of the resource on the first virtualmachine and monitoring the instrumented virtual machine environmentwhile executing the second version of the resource with the malwaresample opened using the second version of the resource is performed. Inan example implementation, the first virtual machine instance can beconfigured to include a set of instructions (e.g., startup instructions,such as in an autoexec.bat file), such as a set of instructions toinstall the second version of the resource (e.g., after a predeterminedperiod of time and/or based on other criteria) and to open the candidatemalware using the second version of the resource. In particular, thecandidate malware can also be analyzed by opening the candidate malwareusing the second version of the resource and monitoring behaviors usingthe instrumented virtual machine environment (e.g., for a predeterminedperiod of time and/or until malicious behavior/activity is detected). Inthis example, the second version of the resource is installed on thefirst virtual machine without having to re-instantiate the first virtualmachine.

In some embodiments, the resource includes an executable application,and the malware sample includes a file in a format that is compatiblewith the executable application (e.g., the application can open themalware sample file). In an example implementation, the instrumentedvirtual machine environment is monitored while executing each version ofthe application with the malware sample opened using each version of theapplication for at least a predetermined period of time or untilmalicious behavior is detected (e.g., and/or until some other criteriais satisfied). In this example implementation, if there are two versionsof the application, then a six minute period of time can be equallyallocated among each of the two versions of the application, such thatthe malware sample is opened using each of the two versions of themalware sample and monitored for approximately three minutes. Assimilarly discussed above, the virtual machine instance can beconfigured to include a set of (startup) instructions, such as a set ofinstructions to load the candidate malware using each version of theresource (e.g., where malware 130 is a Microsoft Word or PDF document,and the loading of the malware can be configured to be performed foreach version based on a predetermined period of time and/or othercriteria).

In some embodiments, two or more different versions of the resource canbe installed and efficiently executed using the same VM instance usingthe following techniques. First, the system environment (e.g., of the VMinstance) can be scanned (e.g., including files, registry settings,processes, and services) in a clean state (e.g., prior to installing aversion of the resource). Then, the first version of the resource (e.g.,a software application, such as Microsoft Office®) can be installed. Thesystem environment can then be scanned again after completion of theinstallation of the first version of the resource to determine any newitems identified, including, for example, any new files that weresaved/installed by the installation, registry setting changes, processeslaunched, and services installed. For example, these new file relateditems and/or registry key related items can then later be renamed inorder to conceal (e.g., hide) the presence of any such file relateditems and/or registry key related items related to the first version ofthe resource having been installed in the system environment. Afterrenaming and saving each of such new file related items and/or registrykey related items (e.g., using dummy file names and/or dummy directorypaths), and performing various additional techniques for handling anynew process and/or service related items as further described below, thesystem environment is returned to an appearance of a clean state aswould be apparent to a second version of the resource (e.g., as anyitems associated with the first version of the resource have been hiddenfrom detection by the renaming of such items to differentnames/directories and/or renaming any such items to different registrykey name/paths, and/or starting/stopping of any processes and/orservices, such as further described below).

In some cases, certain resources (e.g., Microsoft Office® and/or variousother applications) can install many different files and registry keys.A brute force approach that requires renaming all such items cangenerally be slow and/or resource expensive. As a result, in someembodiments, another approach can be performed that determines a subsetor minimum set of items for renaming to more efficiently perform suchrenaming operations. For example, assume that for a set of new fileslocated in a directory path of C:\Program Files\Microsoft Office\ thatonly “Microsoft Office” needs to be renamed in order to hide all of thefollowing items.

-   C:\Program Files\Microsoft Office\CLIPART\-   C:\Program Files\Microsoft Office\CLIPART\PUB60COR\-   C:\Program Files\Microsoft Office\CLIPART\PUB60COR\AG00004_.GIF-   C:\Program Files\Microsoft Office\CLIPART\PUB60COR\AG00011_.GIF-   C:\Program Files\Microsoft Office\CLIPART\PUB60COR\AG00021_.GIF-   C:\Program Files\Microsoft Office\CLIPART\PUB60COR\AG00037_.GIF-   C:\Program Files\Microsoft Office\CLIPART\PUB60COR\AG00038_.GIF-   C:\Program Files\Microsoft Office\CLIPART\PUB60COR\AG00040_.GIF-   C:\Program Files\Microsoft Office\CLIPART\PUB60COR\AG00052_.GIF-   C:\Program Files\Microsoft Office\CLIPART\PUB60COR\AG00057_.GIF

As another example, assume that for a set of new registry keys locatedin a directory path of HKEY_CURRENT_USER\Software\Microsoft\Office\14.0\that only “14.0” needs to be renamed in order to hide all of thefollowing items.

-   HKEY_CURRENT_USER\Software\Microsoft\Office\14.0\Common\-   HKEY_CURRENT_USER\Software\Microsoft\Office\14.0\Common\DrawAlerts\-   HKEY_CURRENT_USER\Software\Microsoft\Office\14.0\Common\DrawAlerts\FTP    Sites\-   HKEY_CURRENT_USER\Software\Microsoft\Office\14.0\Common\General\-   HKEY_CURRENT_USER\Software\Microsoft\Office\14.0\Common\LCCache\-   HKEY_CURRENT_USER\Software\Microsoft\Office\14.0\Common\LCCache\SmartArt\-   HKEY_CURRENT_USER\Software\Microsoft\Office\14.0\Common\LCCache\SmartArt\1033_\-   HKEY_CURRENT_USER\Software\Microsoft\Office\14.0\Common\LCCache\Themes\-   HKEY_CURRENT_USER\Software\Microsoft\Office\14.0\Common\LCCache\Themes\1033_\-   HKEY_CURRENT_USER\Software\Microsoft\Office\14.0\Common\LCCache\WordDocParts\-   HKEY_CURRENT_USER\Software\Microsoft\Office\14.0\Common\LCCache\WordDocParts\1033\-   HKEY_CURRENT_USER\Software\Microsoft\Office\14.0\Common\LanguageResources\HKEY_CURRENT_USER\Software    \Microsoft\Office\14.0\Common\LanguageResources\EnabledLanguages\

In an example implementation, by using such a minimum rename set forefficiently performing such renaming operations, this process can beperformed three to ten times faster, depending on the virtual machineexecution environment.

In case of any new processes that are identified during a systemenvironment state scan (e.g., after installation of the first version ofthe resource), any such new processes can be stopped before swapping toanother version of the resource (e.g., before launching/executing thesecond version of the resource), and any corresponding new process foranother version of the resource can be started after such a swap (e.g.,after stopping execution of the first version of the resource, andstarting execution of the second version of the resource).

In case of any new services that are identified during a systemenvironment state scan (e.g., after installation of the first version ofthe resource), any such new services can be uninstalled/installedservice, if stopping/starting such services is not sufficient toproperly execute another version of the resource (e.g., after stoppingexecution of the first version of the resource, and starting executionof the second version of the resource).

As such, using the above-described techniques, two different versions ofthe resource can be installed and efficiently executed using the same VMinstance. As would now be apparent to those of ordinary skill in theart, these renaming and service/process start/stop operations can beperformed to swap between different versions of the resource (e.g.,swapping from an execution of the first version of the resource to anexecution of the second version of the resource and vice versa, suchthat if a selected version of the resource is to be executed, then thefiles/registry keys associated with the selected version of the resourcethat had been renamed to, for example, various dummy file names, can berenamed to expected file names so that the selected version of theresource can execute properly). As would also now be apparent to thoseof ordinary skill in the art, this process of scanning the systemenvironment and performing the above-described resource version specificrelated operations (e.g., renaming of certain files and registry keys,starting/stopping of certain services and/or processes, etc., tofacilitate proper execution of different versions of the resource in thesystem environment) can be repeated to support installation andexecution of additional versions of the resource using the same VMinstance.

At 310, a determination is made as to whether the candidate malware ismalware (e.g., by detecting whether the candidate malware is performingmalicious behavior or activity in the instrumented virtual environment).For example, data resulting from the executing of the virtual machineinstance executing two different versions of the resource for openingthe candidate malware is captured. In particular, the inserting ofkernel level and/or user level hooks in the instrumented virtual machineenvironment can be implemented to facilitate analysis of malwaresamples. Such hooks may be frequently updated (e.g., by the operator ofservice 122). In an example implementation, inserting the hooks justprior to execution is efficient, and can also mitigate attempts bymalware 130 to determine that it is operating in an instrumented (i.e.,hooked) environment (e.g., as certain malware attempt to utilize anti-VMtechniques to evade detection in VM environments). As one example, at306 and/or 308, any modifications to the file system are captured. Asanother example, at 306 and/or 308, any hooks installed in theinstrumented virtual machine environment can report log information(e.g., back to appliance 102 and/or cloud security service 122) foranalysis. As yet another example, at 306 and/or 308, network traffic canbe captured and logged (e.g., using pcap).

Analyses of the results of emulating the sample are then performed. Insome embodiments, various heuristic techniques are used to analyze theresults of emulating the sample in order to detect whether the candidatemalware (e.g., malware sample can include a file, which can be openedusing an appropriate application, and/or a program, such as a script orother executable code or script) executing in the instrumented virtualmachine environment is malware (e.g., by detecting whether the candidatemalware is performing malicious behavior by monitoring the instrumentedvirtual machine environment). As explained above, conclusions can bemade as to whether the samples are malicious, and signatures can begenerated for future use. The virtual machine instance can then beabandoned and new virtual machine instances can be used to evaluate newmalware samples using the techniques disclosed herein.

And, if a determination is made that the candidate malware is malware,then at 310, output is generated that indicates that the candidatemalware is malware (e.g., based at least in part on a determination thatthe candidate malware is associated with malicious behavior(s)). As oneexample, at 310, a signature for the attachment can also be generated(e.g., as an MD5 hash-based signature). As another example, instead ofor in addition to generating a signature, an alert can be generated thatinstructs data appliance 102 not to provide the attachment to client104.

FIG. 4 is another flow diagram of a process for providing detection ofmalware using an instrumented virtual machine environment in accordancewith some embodiments. In various embodiments, process 400 is performedby malware analysis system 132. The process begins at 402 when candidatemalware (e.g., a malware sample) is received. As one example, candidatemalware is received at 402 when an email (e.g., including an attachment)is received by data appliance 102 from system 120. As another example,data appliance 102 can be configured to transmit the attachment toservice 122 for analysis. In that scenario, the candidate malware isreceived by cloud security service 122 at 402.

At 404, storing a plurality of installed versions of a resource usingdummy file names for one or more registry files and one or moreexecutable files associated with the resource is performed.

At 406, for each version of the resource to be executed, renaming one ormore of the dummy file names associated with the version of the resourcebeing executed to a predetermined file name is performed. For example,the dummy file names that are needed for properly executing a selectedversion of the resource can be renamed to expected file names so thatthe selected version of the resource can execute properly.

At 408, monitoring the candidate malware sample opened using eachversion of the resource using the instrumented virtual machine (VM)environment is performed. For instance, the candidate malware can beanalyzed using one or more virtual machines by executing each version ofthe resource with the candidate malware sample (e.g., malware sample caninclude a file, which can be opened using each version of the resource,which can be an application program that can open that format of file)in the instrumented virtual machine environment. As an example, thecandidate malware can be executed in one or more virtual machines114-116 and any behaviors logged for analysis by system 132. As anotherexample, the candidate malware can be executed in one or more virtualmachines 126-128 and analyzed by cloud security service 122.

In an example implementation, the virtual machine instance can beconfigured to include a set of instructions (e.g., startup instructions,such as in an autoexec.bat file), such as a set of instructions to loadthe candidate malware using each version of the resource (e.g., wheremalware 130 is a Microsoft Word or PDF document, and the loading of themalware can be configured to be performed for each version based on apredetermined period of time and/or other criteria). In this exampleimplementation, the set of instructions can also include theinstructions to perform the operations described above at 404 and 406.

At 410, a determination is made as to whether the candidate malware ismalware (e.g., by detecting whether the candidate malware is performingmalicious behavior or activity in the instrumented virtual environment).For example, data resulting from the executing of the virtual machineinstance executing two different versions of the resource for openingthe candidate malware is captured, as similarly discussed above. As alsoexplained above, conclusions can be made as to whether the samples aremalicious, and signatures can be generated for future use. The virtualmachine instance can then be abandoned and new virtual machine instancesused to evaluate new malware samples using the techniques disclosedherein.

And, if a determination is made that the candidate malware is malware,then at 410, output is generated that indicates that the candidatemalware is malware (e.g., based at least in part on a determination thatthe candidate malware is associated with malicious behavior(s)). As oneexample, at 410, a signature for the attachment can also be generated(e.g., as an MD5 hash-based signature). As another example, instead ofor in addition to generating a signature, an alert can be generated thatinstructs data appliance 102 not to provide the attachment to client104.

FIG. 5 is another flow diagram of a process for providing detection ofmalware using an instrumented virtual machine environment in accordancewith some embodiments. In various embodiments, process 500 is performedby malware analysis system 132. The process begins at 502 when candidatemalware (e.g., a malware sample) is received. As one example, candidatemalware is received at 502 when an email (e.g., including an attachment)is received by data appliance 102 from system 120. As another example,data appliance 102 can be configured to transmit the attachment toservice 122 for analysis. In that scenario, the candidate malware isreceived by cloud security service 122 at 502.

At 504, preloading one or more system files that are used by a firstversion of a resource and/or a second version of the resource into a newresource system file location directory is performed. For example,preloading one or more system files can include preloading requiredlibraries (e.g., dynamically loaded libraries (DLLs)) into a localdirectory so that a program loader can access those files that would notnecessarily be available if running a certain version of the operatingsystem (e.g., preloading DLLs into a common files\Adobe-X localdirectory such that the Adobe application program loader can access suchDLLs on the Windows 8 virtual machine instance for a legacy version ofthat Adobe application that was configured to execute on Windows XP butnot Windows 8).

At 506, overriding an installer for the resource to redirect theinstaller to the new resource system file location directory isperformed. For example, the installer of the resource can be modified toload a correct version of common resources, such as to redirect theinstaller to access certain directors for loading various system fileswhen installing the resource (e.g., such as for loading certainlibraries or other operating systems and/or resource related librariesor other components used for installing the resource). In particular, toprevent abnormal operation of a selected version of the resource duringexecution, certain common resources often would have to be loaded inorder to properly select the version of the resource (e.g., C:\programfiles\common files\resource-X″ is a directory for files that will beloaded across the versions; such files can place different versions offiles, such as libraries or other common files used by resource-X, underdifferent folders, and redirect the loader to load the correct versionof the resource-X; or such resources can be renamed to the correct pathbefore a given version of the resource-X is executed such that it canfind the correct version of such libraries or other common files used byresource-X). As another example, the installer of the resource can bemodified to bypass a version check during installation (e.g., bydisabling version check installer logic and/or hiding/concealing thefiles/registries that the installer would typically be configured tolook for, etc.).

At 508, monitoring the candidate malware sample opened using eachversion of the resource using the instrumented virtual machine (VM)environment is performed. For instance, the candidate malware can beanalyzed using one or more virtual machines by executing each version ofthe resource with the candidate malware sample (e.g., malware sample caninclude a file, which can be opened using each version of the resource,which can be an application program that can open that format of file)in the instrumented virtual machine environment. As an example, thecandidate malware can be executed in one or more virtual machines114-116 and any behaviors logged for analysis by system 132. As anotherexample, the candidate malware can be executed in one or more virtualmachines 126-128 and analyzed by cloud security service 122.

In an example implementation, the virtual machine instance can beconfigured to include a set of (startup) instructions, such as a set ofinstructions to load the candidate malware using each version of theresource (e.g., where malware 130 is a Microsoft Word or PDF document,and the loading of the malware can be configured to be performed foreach version based on a predetermined period of time and/or othercriteria). In this example implementation, the set of instructions canalso include the instructions to perform the operations described aboveat 504 and 506. In another example implementation, the set ofinstructions can also include the instructions to perform the operationsdescribed above at 404 and 406 as well as to perform the operationsdescribed above at 504 and 506.

At 510, a determination is made as to whether the candidate malware ismalware (e.g., by detecting whether the candidate malware is performingmalicious behavior or activity in the instrumented virtual environment).For example, data resulting from the executing of the virtual machineinstance executing two different versions of the resource for openingthe candidate malware is captured, as similarly discussed above. As alsoexplained above, conclusions can be made as to whether the samples aremalicious, and signatures can be generated for future use. The virtualmachine instance can then be abandoned and new virtual machine instancesused to evaluate new malware samples using the techniques disclosedherein.

And, if a determination is made that the candidate malware is malware,then at 510, output is generated that indicates that the candidatemalware is malware (e.g., based at least in part on a determination thatthe candidate malware is associated with malicious behavior(s)). As oneexample, at 510, a signature for the attachment can also be generated(e.g., as an MD5 hash-based signature). As another example, instead ofor in addition to generating a signature, an alert can be generated thatinstructs data appliance 102 not to provide the attachment to client104.

Although the foregoing embodiments have been described in some detailfor purposes of clarity of understanding, the invention is not limitedto the details provided. There are many alternative ways of implementingthe invention. The disclosed embodiments are illustrative and notrestrictive.

What is claimed is:
 1. A system for detection of malware using aninstrumented virtual machine environment, comprising: a processorconfigured to: instantiate a first virtual machine in the instrumentedvirtual machine environment, wherein the first virtual machine isconfigured to support installation of two or more versions of aresource; preload one or more system files that are used by a firstversion of the resource, a second version of the resource into a newresource system file location directory, or both, comprising to: preloada dynamically loaded library (DLL) used by a version of the resourceinto a local directory, the new resource system file location directorycorresponding to the local directory; override an installer for theresource to redirect the installer to the new resource system filelocation directory, comprising to: modify the installer to load the DLLfrom the new resource system file location directory; install, via theinstaller, the first version of the resource on the first virtualmachine and monitor the instrumented virtual machine environment whileexecuting the first version of the resource with a malware sample openedusing the first version of the resource; install, via the installer, thesecond version of the resource on the first virtual machine and monitorthe instrumented virtual machine environment while executing the secondversion of the resource with the malware sample opened using the secondversion of the resource; and monitor the instrumented virtual machineenvironment while executing each version of the resource with themalware sample opened using each version of the resource; and a memorycoupled to the processor and configured to provide the processor withinstructions.
 2. The system recited in claim 1, wherein the resourceincludes an executable application, and wherein the malware sampleincludes a file in a format that is compatible with the executableapplication.
 3. The system recited in claim 1, wherein the instrumentedvirtual machine environment is monitored while executing each version ofthe resource with the malware sample opened using each version of theresource for at least a predetermined period of time or until maliciousbehavior is detected.
 4. The system recited in claim 1, wherein thesecond version of the resource is installed on the first virtual machinewithout having to re-instantiate the first virtual machine.
 5. Thesystem recited in claim 1, wherein the processor is further configuredto: store a plurality of installed versions of the resource using dummyfile names for one or more registry files and one or more executablefiles associated with the resource; and for each version of the resourceto be executed, rename one or more of the dummy file names associatedwith the version of the resource being executed to a predetermined filename.
 6. The system recited in claim 1, wherein the system executes acloud security service, and wherein the processor is further configuredto: receive the malware sample at the cloud security service from asecurity device, wherein the instrumented virtual machine environment ismonitored during execution of each version of the resource with themalware sample opened using each version of the resource to determinewhether the malware sample indicates potentially malicious behavior. 7.A method for detection of malware using an instrumented virtual machineenvironment, comprising: instantiating a first virtual machine in theinstrumented virtual machine environment, wherein the first virtualmachine is configured to support installation of two or more versions ofa resource; preloading one or more system files that are used by a firstversion of the resource, a second version of the resource into a newresource system file location directory, or both, comprising: preloadinga dynamically loaded library (DLL) used by a version of the resourceinto a local directory, the new resource system file location directorycorresponding to the local directory; overriding an installer for theresource to redirect the installer to the new resource system filelocation directory, comprising: modifying the installer to load the DLLfrom the new resource system file location directory; installing, viathe installer, the first version of the resource on the first virtualmachine and monitoring the instrumented virtual machine environmentwhile executing the first version of the resource with a malware sampleopened using the first version of the resource; installing, via theinstaller, the second version of the resource on the first virtualmachine and monitoring the instrumented virtual machine environmentwhile executing the second version of the resource with the malwaresample opened using the second version of the resource; and monitoringthe instrumented virtual machine environment while executing eachversion of the resource with the malware sample opened using eachversion of the resource.
 8. The method of claim 7, wherein the resourceincludes an executable application, and wherein the malware sampleincludes a file in a format that is compatible with the executableapplication.
 9. The method of claim 7, wherein the instrumented virtualmachine environment is monitored while executing each version of theresource with the malware sample opened using each version of theresource for at least a predetermined period of time or until maliciousbehavior is detected.
 10. The method of claim 7, wherein the secondversion of the resource is installed on the first virtual machinewithout having to re-instantiate the first virtual machine.
 11. Themethod of claim 7, further comprising: storing a plurality of installedversions of the resource using dummy file names for one or more registryfiles and one or more executable files associated with the resource; andfor each version of the resource to be executed, renaming one or more ofthe dummy file names associated with the version of the resource beingexecuted to a predetermined file name.
 12. The method of claim 7,wherein the instrumented virtual machine environment is executed by acloud security service, and further comprising: receiving the malwaresample at the cloud security service from a security device, wherein theinstrumented virtual machine environment is monitored during executionof each version of the resource with the malware sample opened usingeach version of the resource to determine whether the malware sampleindicates potentially malicious behavior.
 13. A computer program productfor detection of malware using an instrumented virtual machineenvironment, the computer program product being embodied in anon-transitory, tangible computer readable storage medium and comprisingcomputer instructions for: instantiating a first virtual machine in theinstrumented virtual machine environment, wherein the first virtualmachine is configured to support installation of two or more versions ofa resource; preloading one or more system files that are used by a firstversion of the resource, a second version of the resource into a newresource system file location directory, or both, comprising: preloadinga dynamically loaded library (DLL) used by a version of the resourceinto a local directory, the new resource system file location directorycorresponding to the local directory; overriding an installer for theresource to redirect the installer to the new resource system filelocation directory, comprising: modifying the installer to load the DLLfrom the new resource system file location directory; installing, viathe installer, the first version of the resource on the first virtualmachine and monitoring the instrumented virtual machine environmentwhile executing the first version of the resource with a malware sampleopened using the first version of the resource; installing, via theinstaller, the second version of the resource on the first virtualmachine and monitoring the instrumented virtual machine environmentwhile executing the second version of the resource with the malwaresample opened using the second version of the resource; and monitoringthe instrumented virtual machine environment while executing eachversion of the resource with the malware sample opened using eachversion of the resource.
 14. The computer program product recited inclaim 13, wherein the resource includes an executable application, andwherein the malware sample includes a file in a format that iscompatible with the executable application.
 15. The computer programproduct recited in claim 13, wherein the instrumented virtual machineenvironment is monitored while executing each version of the resourcewith the malware sample opened using each version of the resource for atleast a predetermined period of time or until malicious behavior isdetected.
 16. The computer program product recited in claim 13, whereinthe second version of the resource is installed on the first virtualmachine without having to re-instantiate the first virtual machine. 17.The computer program product recited in claim 13, further comprisingcomputer instructions for: storing a plurality of installed versions ofthe resource using dummy file names for one or more registry files andone or more executable files associated with the resource; and for eachversion of the resource to be executed, renaming one or more of thedummy file names associated with the version of the resource beingexecuted to a predetermined file name.
 18. The computer program productrecited in claim 13, wherein the instrumented virtual machineenvironment is executed by a cloud security service, and furthercomprising computer instructions for: receiving the malware sample atthe cloud security service from a security device, wherein theinstrumented virtual machine environment is monitored during executionof each version of the resource with the malware sample opened usingeach version of the resource to determine whether the malware sampleindicates potentially malicious behavior.